This textbook addresses the core issues facing economists concerning price determination in commodity markets, especially food and agricultural commodities. This book hones in on the conceptual basis of the various relationships, with special emphasis on market interrelationships, both horizontally and vertically. This book covers key concepts such as consumer demand theory; quality, heterogeneous goods, and cross section demand; derived demand, marketing margins, and relationship between output and raw material prices; retail-to-farm demand linkages, imperfect competition, and short-run price determination; dynamic consumer demand; and dynamic models of the firm. What makes this textbook of particular use to students is its focus on bridging the gap between theory and empirical analysis. Going from theory to empirics requires that we have data—time series or cross section—that match the theoretical constructs. Often the data match is not perfect, either by definition or how the data are computed. In addition to problems of matching data with theoretical constructs, students and researchers need to know how to specify, estimate, and interpret results within the context of imperfect and often incomplete data. This textbook uses several data sets to illustrate how one might address problems in real-world settings. Furthermore, with exercises at the end of each chapter, students are able to test themselves on their ability to bring theory to life.

This textbook addresses the core issues facing economists concerning price determination in commodity markets, especially food and agricultural commodities. This book hones in on the conceptual basis of the various relationships, with special emphasis on market interrelationships, both horizontally and vertically. This book covers key concepts such as consumer demand theory; quality, heterogeneous goods, and cross section demand; derived demand, marketing margins, and relationship between output and raw material prices; retail-to-farm demand linkages, imperfect competition, and short-run price determination; dynamic consumer demand; and dynamic models of the firm. What makes this textbook of particular use to students is its focus on bridging the gap between theory and empirical analysis. Going from theory to empirics requires that we have data—time series or cross section—that match the theoretical constructs. Often the data match is not perfect, either by definition or how the data are computed. In addition to problems of matching data with theoretical constructs, students and researchers need to know how to specify, estimate, and interpret results within the context of imperfect and often incomplete data. This textbook uses several data sets to illustrate how one might address problems in real-world settings. Furthermore, with exercises at the end of each chapter, students are able to test themselves on their ability to bring theory to life.

Using Applied Econometrics with SAS: Modeling Demand, Supply, and Risk, you will quickly master SAS applications for implementing and estimating standard models in the field of econometrics. This guide introduces you to the major theories underpinning applied demand and production economics. For each of its three main topics--demand, supply, and risk--a concise theoretical orientation leads directly into consideration of specific economic models and econometric techniques, collectively covering the following: Double-log demand systems Linear expenditure systems Almost ideal demand systems Rotterdam models Random parameters logit demand models Frequency-severity models Compound distribution models Cobb-Douglas production functions Translogarithmic cost functions Generalized Leontief cost functions Density estimation techniques Copula models SAS procedures that facilitate estimation of demand, supply, and risk models include the following, among others: PROC MODEL PROC COPULA PROC SEVERITY PROC KDE PROC LOGISTIC PROC HPCDM PROC IML PROC REG PROC COUNTREG PROC QLIM An empirical example, SAS programming code, and a complete data set accompany each econometric model, empowering you to practice these techniques while reading. Examples are drawn from both major scholarly studies and business applications so that professors, graduate students, government economic researchers, agricultural analysts, actuaries, and underwriters, among others, will immediately benefit.

In today’s data-driven world, the ability to analyze and interpret data has become an essential skill for individuals and organizations alike. Statistical analysis, which involves using mathematical methods to analyze and draw conclusions from data, is one of the most powerful tools available for this purpose. While statistical analysis can be performed using various software programs, Microsoft Excel remains one of the most widely used tools for data analysis. Its user-friendly interface, versatile features, and widespread availability make it a popular choice for data analysis, especially for those who are new to statistical analysis. This book, “Mastering Statistical Analysis Using Excel,” is designed to provide readers with a comprehensive guide to using Excel for statistical analysis. Whether you are a beginner or an experienced user of Excel, this book will help you master the fundamentals of statistical analysis and learn how to use Excel to perform a wide range of statistical analyses. The book is organized into chapters that cover different statistical techniques, starting with basic descriptive statistics and progressing to more advanced techniques such as hypothesis testing, regression analysis, and ANOVA. Each chapter includes clear explanations of the concepts, step-by-step instructions for performing the analysis in Excel, and examples to illustrate how to apply the techniques to real-world data. Throughout the book, we focus on practical applications of statistical analysis, with a particular emphasis on using Excel to solve real-world problems. We also include tips and tricks for optimizing your use of Excel, including keyboard shortcuts, Excel functions, and add-ins that can help streamline your analysis. We believe that this book will be a valuable resource for anyone looking to improve their skills in statistical analysis using Excel. Whether you are a student, a business professional, or a researcher, the techniques and tools covered in this book will help you gain valuable insights from your data and make informed decisions based on your findings.

International trade is a key dimension of the world economy, it is a critical factor in raising living standards, increasing employment, and providing a larger variety of goods to consumers around the world. Despite the strong focus that international trade research has received in theoretical terms, the empirical aspects of trade are less clear and justify further research. In this context, it is essential for studies to focus on shedding light on the most important methods used to evaluate the multiple dimensions of trade within this international context. Trade has a myriad of direct and indirect effects, therefore touching several fields of research, including economics, management, finance, international relations, political science, and sociology, which makes it essential to explore. The Handbook of Research on the Empirical Aspects of Strategic Trade Negotiations and Management provides a systematic overview of the latest trends in the empirical analysis of trade from international perspectives. It provides a survey on the methods used to evaluate a specific topic in international trade, enhance knowledge about the multiple facets of international trade around the world, and grant in-depth surveys of previous empirical findings on specific topics in international trade. Important topics covered within this book include trade diversification, regional centrality, ethical pricing, globalization, cultural impacts, and open economies. This book is a valuable reference tool for government officials, policy makers, managers, executives, economists, practitioners, stakeholders, researchers, academicians, and students.